Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer’s disease from cognitively unimpaired amyloid-positive individuals

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer’s disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.


Participants
We recruited participants from the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD) and visitors to the dementia clinic of Seoul National University Bundang Hospital (SNUBH) between August 2016 and August 2022.KLOSCAD is a nationwide, prospective cohort study that included a random sample of 6818 Koreans aged ≥ 60 years.The initial assessment was carried out between 2010 and 2012 with biennial follow-ups 25 .We included a total of 180 participants, 45 participants with CU A+ and 135 with prodromal AD matched 1:3 by age, sex, and education.All participants were amyloid-positive, as confirmed by a global standardized uptake value ratio (SUVR) of ≥ 0.96 26 using 18 F-florbetaben PET scans.We excluded participants with major psychiatric and/or neurological disorders other than AD, which could influence cognitive function.This study was approved by the Institutional Review Board of the SNUBH, Seongnam, Korea.We acquired written informed consent from the subjects or their legal guardians.All procedures were performed in accordance with the relevant guidelines and regulations.

Diagnostic evaluation
Geriatric neuropsychiatrists conducted standardized diagnostic interviews that included medical history evaluation, physical examination, and neurological assessment according to the Korean version of the Consortium to Establish a Registry for AD Assessment Packet Clinical Assessment Battery (CERAD-K) 27 .Research neuropsychologists or trained research nurses administered the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet Neuropsychological Assessment Battery (CERAD-K-N) 28,29 , digit span test (DST) 30 , executive clock drawing task (CLOX) 31,32 , and frontal assessment battery 33 to each participant.The CERAD-K-N consists of nine neuropsychological tests: verbal fluency test, 15-item Boston naming test, mini-mental state examination, word list memory test, constructional praxis test, word list recall test, word list recognition test, constructional recall test, and trail making test A/B 28,29 .
A panel of geriatric neuropsychiatrists determined the final diagnosis and clinical dementia rating (CDR) 34 .Cognitive stages were determined by syndrome staging of the cognitive continuum at the National Institute on Aging and Alzheimer's Association (NIA-AA) 4 .CU A + was defined as cognitively unimpaired individuals with a CDR = 0 or neuropsychological performance greater than − 1.5 standard deviations (SD) from the age-, sex-, and education-adjusted norms in all neuropsychological tests.Prodromal AD was identified as MCI when the subject's performance was less than − 1.5 SD of age-, sex-, and education-adjusted norms in any neuropsychological test.
Three-dimensional T1-weighted spoiled gradient-echo MRI was performed using a 3.0 T Achieva Scanner (Philips Medical Systems, Eindhoven, the Netherlands) at SNUBH.The images featured a sagittal slice thickness of 1.0 mm with no gaps between slices, an echo time of 4.6 ms, a repetition time of 8.1 ms, a flip angle of 8°, and a matrix size measuring 175 × 480 × 480 in the x, y, and z dimensions, with a voxel size of 1.0 × 0.5 × 0.5 mm 3 .We converted the original digital imaging and communications in medicine format images to the neuroimaging informatics technology initiative format for analysis using MRIcron software (version 1.0; https:// www.micro.com).Subsequently, we resliced the T1 images to isovoxels sized 1.0 × 1.0 × 1.0 mm 3 .
We used FreeSurfer (version 6.0.0;http:// surfer.nmr.mgh.harva rd.edu) to segment whole-brain structures into brain regions as defined by the Desikan-Killiany-Tourville (DKT) atlas 35 .The process begins with motion correction, nonuniform intensity normalization, and skull stripping.The second stage involves full-scale volumetric labeling and automatic topology fixing.The third stage comprises spherical mapping and cortical parcellation.After completing the recon-all process, we obtained individual parcellated brain masks according to the DKT atlas 36 .We extracted regional volumes of 68 regions of interest (ROIs) of the cerebral cortex 37 and 12 ROIs of the subcortex 36 .

Acquisition of 18 F-florbetaben brain PET scans and regional SUVRs
Amyloid brain PET images with 18 F-florbetaben were performed with a discovery VCT scanner (General Electric Medical Systems; Milwaukee, WI, USA).An intravenous slow bolus injection (6 s/mL) of 8.1 mCi (300 MBq) was administered. 18F-florbetaben (Neuraceq, Piramal, Mumbai, India) was administered in a total volume of up to 10 mL.After a 90-min uptake period, 20-min PET images were captured, consisting of four 5-min dynamic frames.
Images were processed using the FreeSurfer PetSurfer procedure (FreeSurfer version 6.0.0;http:// surfer.nmr.mgh.harva rd.edu/ fswik iPetS urfer/) to perform co-registration, SUVR calculations, and partial volume effect correction (PVC) 38 .In detail, the individual PET was co-registered with the corresponding native T1-weighted MRI using a rigid-body registration with a mutual information cost function.Each individually co-registered PET scan was then scaled by the mean value in the cerebellar reference region to calculate the SUVR.The global SUVR was calculated as the volume-average uptake of five cortical ROIs, including the frontal, parietal, lateral temporal, posterior, and anterior cingulate cortex regions, to the whole-cerebellar reference region 39 .The amyloid-positivity was defined considering the threshold of global SUVR ≥ 0.96 in each individual 26 in this study.Individual SUVR images were corrected for partial volume effects using an extended Müller-Gärtner (MG) method, which estimates the true radioactivity concentration in the gray matter (GM) of the human brain by considering the heterogeneity of the GM activity through a four-compartment model within the PetSurfer procedure.The GM threshold for PVC was set to 0.1, and the point spread function for PVC was estimated to be 4 mm.We computed regional SUVR values from ROIs used for regional volume estimation by MRI using PetSurfer procedure.

Statistical analysis
We compared demographic and clinical characteristics between the two diagnostic groups (CU A+ and prodromal AD groups) using the independent t-test (continuous variables) and chi-square test (categorical variables).We compared the regional SUVR and volume adjusted for intracranial volume (ICV) across all ROIs in the DKT atlas between the two groups using independent t-tests.Subsequent multiple comparisons were conducted using the False Discovery Rate (FDR), establishing a significance threshold for group differences at < 0.1 [40][41][42][43] .Furthermore, we compared the regional mean SUVR in each ROI using a two-way analysis of covariance adjusted for the volume of each ROI.
We then used LASSO logistic regression to identify ROIs associated with prodromal AD in relation to amyloid deposition and regional atrophy.LASSO regression is a technique that emphasizes variables with robust associations with the outcome of interest while identifying the coefficients that should be set to zero, effectively facilitating feature selection and reducing model complexity 44 .All continuous predictor variables, including SUVR and volume values for each ROI, were standardized before fitting the model to ensure comparability and improve the interpretability of the model coefficients.To assess the uncertainty of the model coefficients, we performed a bootstrap analysis with 1000 replications.This approach allowed us to estimate the standard errors and 95% confidence intervals (Cis) for the LASSO logistic regression coefficients by resampling the data with replacement and refitting the model for each replication 45 .We tested three different LASSO logistic regression models: (1) the model included SUVR values for all ROIs; (2) the model included regional volumes of all ROIs; and (3) the model included SUVR and volume of each ROI, along with interaction terms, to explore the interplay between regional amyloid deposition and regional atrophy.
In ROIs that show a significant interaction between regional SUVR and volume, we performed a subgroup analysis.We divided the entire group into high and low SUVR groups according to the median value of SUVR in the respective ROI and analyzed the association between SUVR levels and prodromal AD using binary logistic regression.Similarly, we divided the entire group into the high-and low-volume groups according to the median value of volume in the respective ROI and analyzed the association between volume and prodromal AD.

Results
The mean age of the 180 participants was 76.82 years; 60% were female, and the mean educational level was 12.24 years.In the prodromal AD group, the proportion of apolipoprotein E4 carriers was higher and most neuropsychological test scores were lower than in the CU A+ group; however, these differences were not statistically significant.However, in categorical verbal fluency, constructional praxis, and wordlist recognition tests, the prodromal AD group showed significantly worse performance than the CU A+ group.Although the global SUVR did not differ significantly between the two groups, the total GM volume in the prodromal AD group was significantly lower than in the CU A+ group (Table 1).
After adjusting for multiple comparisons, we found no significant differences in SUVR values across the 80 ROIs in the DKT atlas between the two groups (Table 2, Supplementary Table S1, Fig. S2).However, significant differences in regional volumes were observed in 10 ROIs across the groups: two ROIs in the limbic area (right insula and right parahippocampal gyrus), three ROIs in the temporal lobe (both entorhinal cortices and left inferior temporal gyrus), one ROI in the parietal lobe (right inferior parietal cortex), and four ROIs in the subcortex (both amygdalae and both hippocampi).
In the logistic LASSO regression Model 1, increased SUVRs in the superior parietal cortices and the right precuneus were associated with the likelihood of prodromal AD (Table 3, Fig. 1).In LASSO Model 2, decreased volumes in both the entorhinal cortices, right inferior parietal cortex, both amygdalae, and left hippocampus were associated with prodromal AD diagnosis.In LASSO Model 3, the mean SUVR in the right superior parietal cortex (β = 0.02) and its interaction with regional volume (β = 0.07) were associated with the likelihood of prodromal AD.All selected ROIs in LASSO Model 2 (regional volumes) were retained in LASSO Model 3.
In the subgroup analyses, increased SUVR in the right superior parietal cortex was associated with the higher likelihood of prodromal AD in the population with a low right superior parietal cortex volume (β = 1.215, 95% CI [0.566, 1.876], p < 0.001; Fig. 2).In the population with a high volume of the right superior parietal cortex, the regional SUVR was not associated with the prodromal AD stage (β = − 0.303, 95% CI [− 0.879, 0.272], p = 0.302).

Discussion
In this study, our objective was to explore the regions of the brain that differentiate prodromal AD from CU A+, using regional Aβ SUVR and volume.No ROIs showed a higher SUVR in prodromal AD than in CU A+ group.In contrast, a significant volume reduction in prodromal AD was observed in multiple ROIs including amygdala, www.nature.com/scientificreports/hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices.This suggests that neurodegeneration may be more closely related to the clinical manifestation of AD symptoms in the presence of amyloid positivity, a finding that is also consistent with the amyloid cascade hypothesis 4 .When all ROIs' SUVR and volume, as well as the interaction between SUVR and volume, were input into a LASSO logistic regression model, SUVR in the right superior parietal cortex and volumes in both entorhinal cortices, right inferior parietal cortex, both amygdalae and left hippocampus showed significant associations with prodromal AD stage.In particular, amyloid deposition and regional atrophy interacted significantly with the right superior parietal cortex.This interaction amplified the association between the amount of amyloid deposition and the prodromal AD stage in groups with lower regional volume in the right superior parietal cortex.In our study, SUVRs in the superior parietal cortex (Brodmann areas (BAs) 5 and 7) and right precuneus (BA 7 mesial and a small part of BA 31) were associated with prodromal AD in the LASSO regression (Model 1 in Table 3).These regions correspond to mid to late stages in the staging of amyloid accumulation for cognitively unimpaired individuals 7,8 , and to early-to mid-stages of staging throughout the full dementia spectrum 46 .Prospective studies have confirmed these amyloid staging models to reflect the order of amyloid deposition as the disease progresses 12,13 .
The posterior parietal cortex (BAs 5, 7, 39, and 40), to which these regions belong, has been consistently reported in various studies to exhibit structural, functional, and metabolic changes during the early stages of AD 47 .For example, patients with MCI showed an increase in the precuneus, superior parietal cortex, and supramarginal gyrus activation in both memory and non-memory tasks [48][49][50] .According to the model representing the putative neurobiological mechanisms of parietal vulnerability in the pathogenesis of AD 47 , the parietal lobe  possesses a thinner and more susceptible myelin sheath, rendering it highly vulnerable to myelin breakdown 51,52 .This susceptibility leads to the disconnection between the posterior cingulate gyrus/precuneus and the medial temporal lobe area 47,[53][54][55][56] .Such rupture of axons enhances the deposition of extracellular amyloid 57 , leading to disruptions in glucose metabolism, GM atrophy, and cognitive dysfunction 47 .This model also supports that amyloid accumulation in the regions identified in our study is associated with progression to the symptomatic stage of AD (prodromal AD).
In this study, reduced volumes of the entorhinal cortex, hippocampus, amygdala, and inferior parietal cortex were associated with an increased likelihood of prodromal AD stage.This association persisted even when regional amyloid deposition was incorporated into the LASSO model.These regions are all known to be associated with the conversion from cognitively normal to MCI [58][59][60] .Furthermore, in the early stages of Braak's classification of neurofibrillary tangle accumulation (Stages II-IV) 52,61 , these regions have been identified as significant pathological findings in patients with MCI and those showing memory decline 62 .In a recent study on the AD structural progression MRI staging scheme 63 , these regions have also been identified as belonging to the early stages of atrophy.The study suggests that in addition to local tau accumulation, axonal degeneration in remote sites and other limbic-predominant associated proteinopathies may also influence atrophy at these early stages 63 , which seems applicable to the findings of our study as well.
In a model that included amyloid deposition and regional atrophy, the right superior parietal cortex emerged as the only region where amyloid deposition was associated with prodromal AD.In particular, the interaction between regional volume and amyloid deposition in this region was significantly associated with prodromal AD.In a study focusing on prodromal AD and mild AD dementia, this region has been identified as one of the ROIs where the interaction between amyloid positivity and cortical thickness is significantly correlated with the decrease in CDR-sum of boxes 23 .It is recognized that Aβ and tau AD pathologies contribute to cortical thinning and clinical decline 23 , and observations have shown that phosphorylated tau-dependent cortical thinning occurs in amyloid-positive individuals 64,65 .Moreover, some studies have elucidated that Aβ-associated clinical decline manifests only in the presence of elevated phosphorylated tau 66,67 .Therefore, the reduced regional volume in the right superior parietal cortex, which showed a significant association with prodromal AD through interaction with Aβ, is likely due to tau pathology.Additionally, research indicating that global tau-PET signal intensity, rather than amyloid PET, predicts the rate of subsequent atrophy 68 supports the notion that tau pathology could be a major driver of local neurodegeneration leading to atrophy in the AD brain.
The superior parietal cortex has been traditionally implicated in various cognitive processes 62,69,70 , including sensory integration, visuomotor coordination, higher-order thinking, attention, working memory 71,72 , and episodic memory 73 .As a component of the executive attention network, the superior parietal lobes showed a lower component-related activity in amnestic patients with MCI compared to normal controls 74 .In patients at risk of developing AD, the activity of the superior parietal cortex changes during executive attention-related tasks 48 .A recent study suggests that a connection within the default mode network, particularly between the right superior parietal lobule and the precuneus, may be related to memory capabilities, as indicated by its association with the CDR memory subscale 75 .These functional characteristics of the superior parietal cortex also support the possibility that this region reflects the symptom expression in AD continuums, specifically prodromal AD.
A recent study 76 that observed the asymmetry of amyloid deposition in preclinical AD showed a tendency to leftward lateralization in the preclinical phase, which transitioned to more symmetric accumulation as the disease progressed to the symptomatic stage.Given this background, it is plausible that the more pronounced amyloid deposition in the right-sided regions, including the right superior parietal cortex, when comparing preclinical and prodromal AD, could be attributed to the change from left-sided deposition in the preclinical phase to a more concentrated deposition in the right-sided regions in prodromal AD.
In our study, we implemented a 1:3 matching for age, education, and sex, improving the robustness of our results and effectively minimizing potential confounding variables.Furthermore, by simultaneously examining regional volume and amyloid deposition at the whole-brain level, we were able to identify significant regions and delve into their intricate interactions.Using the LASSO technique in our logistic regression analyses allowed for the selection of the most pertinent variables, thus reducing potential biases from multicollinearity and further strengthening the robustness of our findings.However, the limitations of our study warrant further consideration.First, this study was a cross-sectional study, we were unable to infer causality or direction of effect between Aβ and regional atrophy.Second, we did not examine the potential for interactions between atrophy in one ROI and regional atrophy in a different ROI to reflect progression to prodromal AD.Third, we did not match other potential confounders, such as the APOE genotype or various lifestyle factors, both of which could influence brain amyloid deposition, volume, and advanced clinical stages.Future research should ensure a sufficient sample size matched not only for age, sex, and education but also for ApoE4 status, to facilitate separate analyses based on the presence or absence of the ApoE4 allele.Finally, due to the absence of tau PET data, we were unable to directly investigate the impact of tau pathology on cognitive stage in AD.
This study investigated the impact of amyloid deposition, atrophy, and their interaction in regions associated with the prodromal AD stage compared to CU A+ in the AD continuum.Regional brain atrophy may be more closely associated with the early symptomatic stages of AD than with amyloid deposition, which is consistent with the results of previous studies.The accumulation of amyloid in the right superior parietal cortex, especially with a lower regional volume, could have a substantial association with the symptomatic phase of AD.These findings can be used to identify individuals with symptomatic AD among amyloid-positive individuals using PET and MRI data and can help to understand the pathological processes underlying the progression of AD.
Statistical significance was determined by a two-tailed p-value of less than 0.05 for all analyses.The Statistical Package for the Social Sciences version 25.0 (IBM Corporation; Armonk, NY, USA) and R version 4.2.2(The R Foundation for Statistical Computing; Vienna, Austria) were used for all statistical analyses.

Figure 1 .
Figure 1.18F-florbetaben brain PET images showing high SUVR in (A) right superior parietal cortex (SPC) and (B) right precuneus in prodromal Alzheimer's disease (AD).PET images from one participant with prodromal AD and one age, sex, and education-matched cognitively unimpaired amyloid-positive (CU A+) individual.The white circle indicates the voxel with the largest SUVR difference between CU A+ and prodromal AD.The PET images were coregistered to the individual MRI.The MRI images were subjected to spatial normalization onto the Montreal Neurological Institute (MNI) template using the default unified segmentation methods of Statistical Parametric Mapping (SPM) 12.Using the SPM deformations tool, the computed deformation fields were then applied to the co-registered PET images.The results were normalized PET and MRI images in the MNI space with a voxel size of 2 × 2 × 2 mm 3 .AAL Automated anatomical labelling, CU A+ cognitively unimpaired amyloid-positive, ROI region of interest, SUVR standardized uptake value ratio.

Figure 2 .
Figure 2. Association of SUVR or volume of right superior parietal cortex with the likelihood of prodromal AD according to subgroups.The black squares and horizontal lines correspond to the ORs and 95% confidence intervals.p-value (*) is a result of logistic regression model in each groups.High volume and low volume groups (a) in SUVR of right superior parietal cortex was grouped by median value of volume in right superior parietal cortex.Low SUVR or High SUVR groups (b) in Volume/ICV of right superior parietal cortex was grouped by median value of SUVR in right superior parietal cortex.CI confidence interval, ICV intracranial volume, OR odds ratio, SUVR standardized uptake value ratio.

Table 1 .
Demographic and clinical characteristics of the participants.AD Alzheimer's disease, APOE apolipoprotein E, CU A+ cognitively unimpaired amyloid-positive individual, GMV gray matter volume, ICV intracranial volume, MMSE Mini-Mental State Examination, SD standard deviation, SUVR standardized uptake value ratio.*Independent t-tests for continuous variables, Chi-square tests for categorical variables.

Table 2 .
Comparisons of regional SUVR and volume between cognitively unimpaired amyloid-positive individual and prodromal Alzheimer's disease.AD Alzheimer's disease, CU A+ cognitively unimpaired amyloid-positive individual, ICV intracranial volume, ROI region of interest, SD standard deviation, SUVR standardized uptake value ratio.*OnlyROIsfrom the Desikan-Killiany-Tourville atlas showing significant differences in regional volume or SUVR between the two groups are presented in this table.The comparison results for all ROIs can be found in the Supplementary TableS1.*Standardized data are presented as mean ± SD.
a p < 0.05 from independent t-test between CU A + and prodromal AD. b False Discovery Rate adjusted p value < 0.1 from independent t-test between CU A+ and prodromal AD; no regions of interest were significant at FDR p < 0.05 level.

Table 3 .
Selected variables of logistic LASSO regression models for discriminating prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individual.L left, LASSO least absolute shrinkage and selection operator, R right, ROI region of interest, SUVR standardized uptake value ratio.Model 1 included SUVRs of all sub-ROIs; Model 2 included the volumes of all sub-ROIs, divided by intracranial volume; Model 3 included both the volumes and SUVRs of all sub-ROIs.*Values show β coefficients in each logistic LASSO models.